{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modify chip options"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When creating a new design using Qiskit Metal, a default set of information related to the chip is specified. This includes chip size, which defines the active simulation area in the electromagnetic simulator of your choice. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook we will see how to access and change some of these chip-related specifications to allow you the flexibility of designing your custom quantum chip. We will start by drawing a simple planar design, and then we will play around with chip parameters to highlight the different features accessible through the API."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For convenience, let's begin by enabling [automatic reloading of modules](https://ipython.readthedocs.io/en/stable/config/extensions/autoreload.html?highlight=autoreload) when they change."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's import Qiskit Metal:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <h1 style=\"\n",
       "        background: #12c2e9;  /* fallback for old browsers */\n",
       "        background: -webkit-linear-gradient(to right, #d4418e 0%, #0652c5 74%);  /* Chrome 10-25, Safari 5.1-6 */\n",
       "        background: linear-gradient(315deg, #d4418e 0%, #0652c5 74%); /* W3C, IE 10+/ Edge, Firefox 16+, Chrome 26+, Opera 12+, Safari 7+ */\n",
       "        margin-top: 50px;\n",
       "        border-style: outset;\n",
       "        padding-top:100px;\n",
       "        padding-bottom:50px;\n",
       "        padding-left:25px;\n",
       "        color: white;\n",
       "    \"> Welcome to Qiskit Metal! <h1>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import qiskit_metal as metal\n",
    "from qiskit_metal import designs, draw\n",
    "from qiskit_metal import Dict, open_docs\n",
    "\n",
    "%metal_heading Welcome to Qiskit Metal!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us draw our simple planar design: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "design = designs.DesignPlanar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select a QComponent to create (The QComponent is a python class named `TransmonPocket`)\n",
    "from qiskit_metal.qlibrary.qubits.transmon_pocket import TransmonPocket"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a new qcomponent object with name 'Q1' \n",
    "q1 = TransmonPocket(design, 'Q1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have defined a simple planar design, we can use the following commands to access the dictionary keys to locate a chip and then access the chip-related parameters avaialble to be modified:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['main'])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.chips.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'material': 'silicon',\n",
       " 'layer_start': '0',\n",
       " 'layer_end': '2048',\n",
       " 'size': {'center_x': '0.0mm',\n",
       "  'center_y': '0.0mm',\n",
       "  'center_z': '0.0mm',\n",
       "  'size_x': '9mm',\n",
       "  'size_y': '6mm',\n",
       "  'size_z': '-750um',\n",
       "  'sample_holder_top': '890um',\n",
       "  'sample_holder_bottom': '1650um'}}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.chips.main"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we can see there are four different parameters available for us to change:\n",
    "- Material\n",
    "- Layer_start\n",
    "- Layer_end\n",
    "- Size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to change your wafer material from silicon to germanium, for example, you can run the following code block: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "design.chips.main.material = ['germanium']\n",
    "design.rebuild()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, if we check our chip parameters again, we will see a different item under material. Let's try it out!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'material': ['germanium'],\n",
       " 'layer_start': '0',\n",
       " 'layer_end': '2048',\n",
       " 'size': {'center_x': '0.0mm',\n",
       "  'center_y': '0.0mm',\n",
       "  'center_z': '0.0mm',\n",
       "  'size_x': '9mm',\n",
       "  'size_y': '6mm',\n",
       "  'size_z': '-750um',\n",
       "  'sample_holder_top': '890um',\n",
       "  'sample_holder_bottom': '1650um'}}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.chips.main"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now know how to modify the arguments related to the chip. The most common parameter we may find ourselves dealing with is the chip size. Once we have an idea about our experimental design, choosing a chip size that allows us sufficent space to place all the components as desired is important. Here are the different parameters related to the chip size. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'center_x': '0.0mm',\n",
       " 'center_y': '0.0mm',\n",
       " 'center_z': '0.0mm',\n",
       " 'size_x': '9mm',\n",
       " 'size_y': '6mm',\n",
       " 'size_z': '-750um',\n",
       " 'sample_holder_top': '890um',\n",
       " 'sample_holder_bottom': '1650um'}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.chips.main.size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The parameters 'sample_holder_top' and 'sample_holder_bottom' are placeholders for parameters that specify the top and bottom coordinates of the 'vacuum box' in a multilevel system. The other parameters are self-explanatory. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let us play around with chip-size and export these files to GDS to look at the effects of our commands. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We will begin by resetting the wafer material to silicon\n",
    "\n",
    "design.chips.main.material = ['silicon']\n",
    "design.rebuild()\n",
    "\n",
    "# We will then export the current file to a GDS file\n",
    "a_gds = design.renderers.gds\n",
    "a_gds.options['path_filename'] = '../../resources/Fake_Junctions.GDS'\n",
    "\n",
    "design.renderers.gds.export_to_gds(\"Before_size_change.gds\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will change the size of the chip in x and y dimensions, and then export it as a second GDS file. This can be done as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "design.chips.main.size['size_x'] = '15mm'\n",
    "design.chips.main.size['size_y'] = '10mm'\n",
    "design.rebuild()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.renderers.gds.export_to_gds(\"After_size_x_y_change.gds\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will now move the center of the chip and see the effect it has on the qubit design. We will export this change as a third GDS file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "09:22AM 24s WARNING [_cheese_buffer_maker]: The bounding box for no-cheese is outside of chip size.\n",
      "Bounding box for chip is (0.0, -1.0, 9.0, 5.0).\n",
      "Bounding box with no_cheese buffer is (-0.35000000000000003, -0.35000000000000003, 0.35000000000000003, 0.35000000000000003).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First we will rest to the original settings\n",
    "\n",
    "design.chips.main.size['size_x'] = '9mm'\n",
    "design.chips.main.size['size_y'] = '6mm'\n",
    "\n",
    "# Next we will shift the center of the chip\n",
    "\n",
    "design.chips.main.size['center_x'] = '4.5mm'\n",
    "design.chips.main.size['center_y'] = '2mm'\n",
    "design.rebuild()\n",
    "\n",
    "# We next export it to GDS\n",
    "\n",
    "design.renderers.gds.export_to_gds(\"After_center_x_y_change.gds\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now is a good time to take a look at the three GDS files we have created so far. In our previous run we intentionally centered the chip such that the entire device is not on the chip. This triggers a warning and enables you to make a correction. \n",
    "\n",
    "This warning is triggered by no-cheese check which is always 'ON' by default for the 'main' chip and for level '1'. Cheesing is the process of adding flux holes to the wafer to allow access to the ground plane. So, no_cheese is the “keep-out” region on the chip where the holes would not be implemented. If you have a multiple chip device, this option needs to be modified to match your configuration. We will see how to access and change this setting below. We first look at the GDS rendering options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'short_segments_to_not_fillet': 'True',\n",
       " 'check_short_segments_by_scaling_fillet': '2.0',\n",
       " 'gds_unit': 0.001,\n",
       " 'ground_plane': 'True',\n",
       " 'negative_mask': {'main': []},\n",
       " 'corners': 'circular bend',\n",
       " 'tolerance': '0.00001',\n",
       " 'precision': '0.000000001',\n",
       " 'width_LineString': '10um',\n",
       " 'path_filename': '../../resources/Fake_Junctions.GDS',\n",
       " 'junction_pad_overlap': '5um',\n",
       " 'max_points': '199',\n",
       " 'cheese': {'datatype': '100',\n",
       "  'shape': '0',\n",
       "  'cheese_0_x': '25um',\n",
       "  'cheese_0_y': '25um',\n",
       "  'cheese_1_radius': '100um',\n",
       "  'view_in_file': {'main': {1: True}},\n",
       "  'delta_x': '100um',\n",
       "  'delta_y': '100um',\n",
       "  'edge_nocheese': '200um'},\n",
       " 'no_cheese': {'datatype': '99',\n",
       "  'buffer': '25um',\n",
       "  'cap_style': '2',\n",
       "  'join_style': '2',\n",
       "  'view_in_file': {'main': {1: True}}},\n",
       " 'bounding_box_scale_x': '1.2',\n",
       " 'bounding_box_scale_y': '1.2'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_gds.options"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We notice the dictionary called 'cheese' and 'no_cheese' above. We are interested in the 'view_in_file' option. We show how to access this option below. For a multilayer device, each chip and layer needs to be set to 'True'. If this 'view_in_file' check is 'False', we will not see the warning message we saw above. Let us try it out!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "a_gds.options.no_cheese['view_in_file']['main']={1: False}\n",
    "a_gds.options.cheese['view_in_file']['main']={1: False}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now when we export to GDS, we do not see a warning message."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "design.renderers.gds.export_to_gds(\"After_center_x_y_change_no_warning.gds\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we revert back the 'cheese' and 'no_cheese' dictionaries and overwrite our last GDS with a modified one so that the device is within the chip."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Restore a_gds options\n",
    "\n",
    "a_gds.options.no_cheese['view_in_file']['main']={1: True}\n",
    "a_gds.options.cheese['view_in_file']['main']={1: True}\n",
    "\n",
    "# We will shift the center of the chip to origin\n",
    "\n",
    "design.chips.main.size['center_x'] = '0mm'\n",
    "design.chips.main.size['center_y'] = '0mm'\n",
    "design.rebuild()\n",
    "\n",
    "# We next export it to GDS\n",
    "\n",
    "design.renderers.gds.export_to_gds(\"After_reverting_x_y_change.gds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from qiskit_metal import MetalGUI\n",
    "gui = MetalGUI(design)\n",
    "gui.autoscale()\n",
    "gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You have now restored the chip to its original configuration!"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
